Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Lanlan Kang"'
Publikováno v:
IEEE Access, Vol 7, Pp 59504-59513 (2019)
Gaussian process regression (GPR) is frequently used for uncertain measurement and prediction of nonstationary time series in the Internet of Things data, nevertheless, the generalization and regression efficacy of GPR are directly impacted by its se
Externí odkaz:
https://doaj.org/article/dab2e4c6402240b5a62824de5ff3c8c8
Publikováno v:
IEEE Access, Vol 7, Pp 124397-124409 (2019)
The overwhelming increase of population will lead to an increase network traffic usage. In most products, local cache mechanism is implemented for the purpose of reducing the network traffics. However, Due to storage space limitations, lot of times,
Externí odkaz:
https://doaj.org/article/c158fa5bd6864fb49c0b2cefe0cef6a9
Publikováno v:
Information Sciences. 610:144-155
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e460468a0c2f86d86fdf6ff1dba2a79
https://doi.org/10.1016/j.ins.2022.07.168
https://doi.org/10.1016/j.ins.2022.07.168
Publikováno v:
The Journal of Supercomputing. 77:7440-7454
Since the particle swarm optimization (PSO) was proposed to overcome the inherent defects of PSO such as premature convergence and dependent on parameters settings, different PSO variants are devised to optimize different complex optimization problem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a53dee4a4fd1d6194ea3688f08464a5a
https://doi.org/10.1007/s11227-020-03531-4
https://doi.org/10.1007/s11227-020-03531-4
Publikováno v:
Information Sciences. 533:138-149
Anomaly detection is an important application field of evolutionary algorithm. Unlike traditionly anomaly detection, group anomaly detection aims to discover the anomalous aggregate behaviors in data points. Over past decades, a large number of promi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8808c80746f4756a980221ac887ebcf0
https://doi.org/10.1016/j.ins.2020.03.110
https://doi.org/10.1016/j.ins.2020.03.110
Publikováno v:
International Journal of Grid and Utility Computing. 14:107
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::48a5485b47908ca49188f434f696c2af
https://doi.org/10.1504/ijguc.2023.131010
https://doi.org/10.1504/ijguc.2023.131010
Publikováno v:
International Journal of Grid and Utility Computing. 14:169
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::767e611b4e33a9ceee629a31b3ff3fa0
https://doi.org/10.1504/ijguc.2023.10056303
https://doi.org/10.1504/ijguc.2023.10056303
Publikováno v:
Enterprise Information Systems. 16:326-346
In recent years, the model of improved GAN has been widely applied in the field of machine vision. It not only covers the traditional image processing, but also includes image conversion, image syn...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a351739d409aae8d0eac5a03194ad419
https://doi.org/10.1080/17517575.2019.1701714
https://doi.org/10.1080/17517575.2019.1701714
Publikováno v:
IEEE Access, Vol 7, Pp 124397-124409 (2019)
The overwhelming increase of population will lead to an increase network traffic usage. In most products, local cache mechanism is implemented for the purpose of reducing the network traffics. However, Due to storage space limitations, lot of times,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e594b034cc985a53fdc19b98cdaaba6f
https://ieeexplore.ieee.org/document/8817950/
https://ieeexplore.ieee.org/document/8817950/
Publikováno v:
IEEE Access, Vol 7, Pp 59504-59513 (2019)
Gaussian process regression (GPR) is frequently used for uncertain measurement and prediction of nonstationary time series in the Internet of Things data, nevertheless, the generalization and regression efficacy of GPR are directly impacted by its se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b600900fc3e4ed9a1034ed53cb1938e4
https://ieeexplore.ieee.org/document/8701439/
https://ieeexplore.ieee.org/document/8701439/